measure: BM25 lexical leg vs semseed baseline - net +2 (q10,q11), NOT-SHOWN
hit@5 68.6% -> 74.3%, phrase 71.4% -> 100%, MRR@10 0.461 -> 0.502, latency p50 0.97x. Zero losses, zero run-to-run drift on both sides. 2 queries moved against a 6-query noise floor: NO MEASURABLE DIFFERENCE by the harness's own test (McNemar exact p=0.50). Unaddressable records in returned slots: 57 -> 0. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
This commit is contained in:
Tim Lingo
@@ -0,0 +1,147 @@
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@@ -0,0 +1,959 @@
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{
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"label": "bm25lex-r2",
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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|
||||
{
|
||||
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||||
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|
||||
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|
||||
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|
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
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|
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|
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@@ -0,0 +1,959 @@
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{
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|
||||
"hit@5": 1.0,
|
||||
"recall@5": 0.07692307692307693,
|
||||
"recall@10": 0.3076923076923077,
|
||||
"precision@5": 0.2,
|
||||
"mrr@10": 0.25
|
||||
},
|
||||
{
|
||||
"id": "q29",
|
||||
"category": "associative",
|
||||
"query": "Sarah Bishop Dyer trailer performance",
|
||||
"returned": [
|
||||
"kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
|
||||
"kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
|
||||
"kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
|
||||
"kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
|
||||
"766de879-f9d0-4a07-b6df-b43ee13763d8",
|
||||
"015644f5-8194-4af0-800d-dd4a0cd71396",
|
||||
"tag-trailer-park-paladins",
|
||||
"kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
|
||||
"project-trailer-park-paladins",
|
||||
"kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c"
|
||||
],
|
||||
"n_returned": 10,
|
||||
"latency_ms": 1184.4,
|
||||
"error": null,
|
||||
"hit@5": 1.0,
|
||||
"recall@5": 0.18181818181818182,
|
||||
"recall@10": 0.45454545454545453,
|
||||
"precision@5": 0.4,
|
||||
"mrr@10": 0.5
|
||||
},
|
||||
{
|
||||
"id": "q30",
|
||||
"category": "associative",
|
||||
"query": "Swarm Architecture containment lateral worker",
|
||||
"returned": [
|
||||
"bl-0fac287f-f4c0-4f15-bc4d-ff7f8a7af3ae",
|
||||
"bl-9bde67c1-f0ba-4c3a-8fe5-de0deee0ce43",
|
||||
"bl-2515d870-e35e-443b-ba20-5150bbc73fed",
|
||||
"kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
|
||||
"kn-b36902cc-0b05-44ba-9aa7-800e5dea9ca9",
|
||||
"bl-bea7473c-c687-414c-9c0b-00c509a616c1",
|
||||
"bl-fc6fcb0b-9e4b-40bf-8e88-dbfe4e27c31a",
|
||||
"kn-6f248a50-355b-47bb-aec8-e0e646a9b077",
|
||||
"kn-6061318f-046b-4935-907d-8eafdce14930",
|
||||
"mem-ab34c2f7-3243-424b-affa-25555f6cf9cc"
|
||||
],
|
||||
"n_returned": 10,
|
||||
"latency_ms": 1185.7,
|
||||
"error": null,
|
||||
"hit@5": 0.0,
|
||||
"recall@5": 0.0,
|
||||
"recall@10": 0.0,
|
||||
"precision@5": 0.0,
|
||||
"mrr@10": 0.0
|
||||
},
|
||||
{
|
||||
"id": "q31",
|
||||
"category": "associative",
|
||||
"query": "hope won inside the narrative preface",
|
||||
"returned": [
|
||||
"kn-e0423482-cfa5-4796-8689-8495c93b66bc",
|
||||
"knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
|
||||
"bl-2b00aeb0-c0fa-4a9f-8f30-4207e98b3d52",
|
||||
"kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
|
||||
"kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
|
||||
"knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
|
||||
"knw-723551f5-1950-42a3-8b89-b6a06913cef0",
|
||||
"tag-hope",
|
||||
"knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
|
||||
"kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e"
|
||||
],
|
||||
"n_returned": 10,
|
||||
"latency_ms": 1199.5,
|
||||
"error": null,
|
||||
"hit@5": 1.0,
|
||||
"recall@5": 0.09090909090909091,
|
||||
"recall@10": 0.18181818181818182,
|
||||
"precision@5": 0.2,
|
||||
"mrr@10": 0.25
|
||||
},
|
||||
{
|
||||
"id": "q32",
|
||||
"category": "associative",
|
||||
"query": "man of the house six years old expectation",
|
||||
"returned": [
|
||||
"kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
|
||||
"knw-729fc901-8335-44c4-9f3a-b150b4aa0915",
|
||||
"knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
|
||||
"knw-528dbc37-eabc-4b75-a7a5-65bf38d6018a",
|
||||
"knw-35940684-abc4-42f0-b942-818f66b1f69a",
|
||||
"knw-473f3f24-20f6-4f39-8589-3709538eb6ac",
|
||||
"?Z?<S???K ?",
|
||||
"knw-7902acca-604e-409b-8faf-ad85424211d0",
|
||||
"'?T?a\"B~-?8",
|
||||
"kn-6061318f-046b-4935-907d-8eafdce14930"
|
||||
],
|
||||
"n_returned": 10,
|
||||
"latency_ms": 1422.0,
|
||||
"error": null,
|
||||
"hit@5": 0.0,
|
||||
"recall@5": 0.0,
|
||||
"recall@10": 0.0,
|
||||
"precision@5": 0.0,
|
||||
"mrr@10": 0.0
|
||||
},
|
||||
{
|
||||
"id": "q33",
|
||||
"category": "nonsense",
|
||||
"query": "zqxjvw plimforth grebulon",
|
||||
"returned": [],
|
||||
"n_returned": 0,
|
||||
"latency_ms": 703.8,
|
||||
"error": null,
|
||||
"clean": true,
|
||||
"false_positives": 0
|
||||
},
|
||||
{
|
||||
"id": "q34",
|
||||
"category": "nonsense",
|
||||
"query": "flarnbistle quommetry",
|
||||
"returned": [],
|
||||
"n_returned": 0,
|
||||
"latency_ms": 488.0,
|
||||
"error": null,
|
||||
"clean": true,
|
||||
"false_positives": 0
|
||||
},
|
||||
{
|
||||
"id": "q35",
|
||||
"category": "nonsense",
|
||||
"query": "xxqzzt vurblenacht throom",
|
||||
"returned": [
|
||||
"bl-4476e856-c567-4b49-8ff7-d7dca3e5715e",
|
||||
"?V?",
|
||||
"knw-6b48dce2-f21c-452a-9db5-4e6aa61c87ca",
|
||||
"knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
|
||||
"?m?\\}Q??6??",
|
||||
"8cbb60c5-4999-4ec1-8682-2592aedc4249",
|
||||
"kn-66a21179-2adc-4b19-a109-880cf4674d7d",
|
||||
"?m?\\}Q??6??",
|
||||
"knw-723551f5-1950-42a3-8b89-b6a06913cef0",
|
||||
"kn-333542cb-6dab-4662-9725-bf7440d28bf7"
|
||||
],
|
||||
"n_returned": 10,
|
||||
"latency_ms": 720.7,
|
||||
"error": null,
|
||||
"clean": false,
|
||||
"false_positives": 10
|
||||
},
|
||||
{
|
||||
"id": "q36",
|
||||
"category": "superseded",
|
||||
"query": "is the self-improvement architecture called DARMA or DHARMA",
|
||||
"returned": [
|
||||
"mem-f3b37427-b7d1-4f7e-b32c-0241a20ce8da",
|
||||
"mem-80d7416b-20e9-48a0-b176-b215527e2f56",
|
||||
"tag-__darma____cgi____patents____self-improvement____character-preservation____autonomous____architecture__",
|
||||
"kn-b7e98d63-8b83-4911-b4d0-990602a7f575",
|
||||
"tag-__darma____cgi____patents____self-improvement____character-preservation____autonomous____kotlin____architecture__",
|
||||
"knw-e047bb42-dc5b-4383-9e88-e508dc03abe3",
|
||||
"mem-e6327f52-2bda-4ce7-9471-2fffd1e172de",
|
||||
"bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
|
||||
"mem-82b93b21-a865-410f-9ec1-fc54121d9bb5",
|
||||
"bl-145a0985-2382-400f-a7c5-c335c5e30a72"
|
||||
],
|
||||
"n_returned": 10,
|
||||
"latency_ms": 1301.5,
|
||||
"error": null,
|
||||
"hit@5": 1.0,
|
||||
"recall@5": 1.0,
|
||||
"recall@10": 1.0,
|
||||
"precision@5": 0.2,
|
||||
"mrr@10": 0.5,
|
||||
"outranks": true,
|
||||
"rank_correct": 2,
|
||||
"rank_stale": 8
|
||||
},
|
||||
{
|
||||
"id": "q37",
|
||||
"category": "superseded",
|
||||
"query": "how many provisional patents does Will actually have",
|
||||
"returned": [
|
||||
"mem-6f0b2b45-90c1-4356-ac01-3daac05b09c8",
|
||||
"12082f7e-e320-438b-bd65-083d8259748f",
|
||||
"015644f5-8194-4af0-800d-dd4a0cd71396",
|
||||
"13705072-4515-4124-963d-083af490494f",
|
||||
"527ecb25-2587-47eb-8269-73be2431abd4",
|
||||
"6de314bf-5c4c-4cfc-871f-fa2e422d45e6",
|
||||
"a1000001-0000-0000-0000-000000000002",
|
||||
"3cf706a1-3825-45d8-b0a9-06cae6cdf5b8",
|
||||
"kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
|
||||
"7ac62daa-2eac-4c7a-a97e-e4203fc1b57b"
|
||||
],
|
||||
"n_returned": 10,
|
||||
"latency_ms": 1651.7,
|
||||
"error": null,
|
||||
"hit@5": 0.0,
|
||||
"recall@5": 0.0,
|
||||
"recall@10": 1.0,
|
||||
"precision@5": 0.0,
|
||||
"mrr@10": 0.125,
|
||||
"outranks": true,
|
||||
"rank_correct": 8,
|
||||
"rank_stale": null
|
||||
},
|
||||
{
|
||||
"id": "q38",
|
||||
"category": "superseded",
|
||||
"query": "is MCP still the live integration layer",
|
||||
"returned": [
|
||||
"5fcba804-eb5b-48ec-82da-146b1c6bb50d",
|
||||
"bl-7328cbe3-0200-43c2-88e7-0a164e15fca4",
|
||||
"bl-c8c19362-430b-4817-9cf4-9e85e0099c64",
|
||||
"bl-c5c6571e-118f-47c7-8cbb-3ed0ebf64a51",
|
||||
"mem-101e81b4-8097-4749-8d8d-7bb66de34517",
|
||||
"ctx-3a55",
|
||||
"86228228-7adf-41fb-b4c4-9ceea87953ae",
|
||||
"4509ed62-9fb2-48b8-9038-ac569fca9604",
|
||||
"bl-4f7b651b-6b33-449c-8a3b-cfce12ce984b",
|
||||
"mem-3a2cf162-d93b-4f29-86f2-5066fb7fe1f5"
|
||||
],
|
||||
"n_returned": 10,
|
||||
"latency_ms": 1021.6,
|
||||
"error": null,
|
||||
"hit@5": 0.0,
|
||||
"recall@5": 0.0,
|
||||
"recall@10": 0.0,
|
||||
"precision@5": 0.0,
|
||||
"mrr@10": 0.0,
|
||||
"outranks": false,
|
||||
"rank_correct": null,
|
||||
"rank_stale": 5
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,142 @@
|
||||
import numpy as np, json, urllib.request, collections, math, re, sys, time
|
||||
SP="/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad"
|
||||
EV="/Users/timlingo/Development/neuron-technologies/_wt-semseed/tools/retrieval-eval/"
|
||||
np.seterr(all='ignore')
|
||||
t0=time.time()
|
||||
M=np.load(SP+'/emb.npy'); eids=open(SP+'/ids.txt',encoding='utf-8',errors='surrogateescape').read().split('\n')
|
||||
eidx={k:i for i,k in enumerate(eids)}
|
||||
d=json.load(open('/Users/timlingo/neuron-memory-backups/snapshot-pre-repair-20260806.json',encoding='utf-8',errors='surrogateescape'))
|
||||
print("loaded corpus %.1fs"%(time.time()-t0),file=sys.stderr)
|
||||
STRUCT={"identity","contains","superseded_by","references","embodies","demonstrated_by","canonical-self","depends_on","currently_holds","activates"}
|
||||
adj=collections.defaultdict(list)
|
||||
for e in d['edges']:
|
||||
if e.get('relation') not in STRUCT: continue
|
||||
w=float(e.get('weight') or 0.0)
|
||||
adj[e['from_id']].append((e['to_id'],w)); adj[e['to_id']].append((e['from_id'],w))
|
||||
nodes=d['nodes']
|
||||
N={n['id']:n for n in nodes}
|
||||
PRINT=re.compile(r'^[\x20-\x7e]+$')
|
||||
ids=[]; hay=[]; dl=[]; sal=[]; addressable=[]
|
||||
for n in nodes:
|
||||
i=n.get('id') or ''
|
||||
h=((n.get('content') or '')+'\x00'+(n.get('label') or '')+'\x00'+(n.get('tags') or '')).lower()
|
||||
ids.append(i); hay.append(h); dl.append(len(h)); sal.append(float(n.get('salience') or 0.0))
|
||||
addressable.append(bool(PRINT.match(i)))
|
||||
del d
|
||||
NN=len(ids); avgdl=sum(dl)/NN
|
||||
print("nodes=%d avgdl=%.0f addressable=%d %.1fs"%(NN,avgdl,sum(addressable),time.time()-t0),file=sys.stderr)
|
||||
gold={q['id']:q for q in json.load(open(EV+"gold_set.json"))['queries']}
|
||||
LEXMAIN={r['id']:r['returned'] for r in json.load(open(EV+"results-main.json"),) ['rows']} if False else {r['id']:r['returned'] for r in json.load(open(EV+"results-main.json",encoding='utf-8',errors='surrogateescape'))['rows']}
|
||||
CACHE={}
|
||||
def emb(t):
|
||||
if t in CACHE: return CACHE[t]
|
||||
b=json.dumps({"model":"nomic-embed-text","prompt":t}).encode()
|
||||
r=urllib.request.Request("http://127.0.0.1:11434/api/embeddings",data=b,headers={"Content-Type":"application/json"})
|
||||
v=np.array(json.load(urllib.request.urlopen(r,timeout=60))["embedding"],dtype=np.float32)
|
||||
v=v/(np.linalg.norm(v)+1e-9); CACHE[t]=v; return v
|
||||
K1,B=1.2,0.75
|
||||
def lexleg(query, mode, guard, lim=10):
|
||||
toks=[]
|
||||
for w in query.split():
|
||||
wl=w.lower()
|
||||
if wl not in toks: toks.append(wl)
|
||||
nt=len(toks)
|
||||
masks=[]; df=[0]*nt
|
||||
for i in range(NN):
|
||||
if guard and not addressable[i]: continue
|
||||
h=hay[i]; m=0; sc=0
|
||||
for t in range(nt):
|
||||
if toks[t] in h: m|=(1<<t); sc+=1; df[t]+=1
|
||||
if sc: masks.append((i,m,sc))
|
||||
if mode=='tokcount':
|
||||
masks.sort(key=lambda x:(-x[2], -sal[x[0]]))
|
||||
return [ids[i] for i,m,sc in masks[:lim]]
|
||||
idf=[math.log(1.0+(NN-df[t]+0.5)/(df[t]+0.5)) for t in range(nt)]
|
||||
scored=[]
|
||||
for i,m,sc in masks:
|
||||
norm=1.0-B+B*dl[i]/avgdl
|
||||
s=0.0
|
||||
for t in range(nt):
|
||||
if m&(1<<t): s+=idf[t]*(K1+1.0)/(1.0+K1*norm)
|
||||
scored.append((s,i))
|
||||
scored.sort(key=lambda x:(-x[0], -sal[x[1]]))
|
||||
return [ids[i] for s,i in scored[:lim]]
|
||||
FIRE=0.02; DECAY=0.7; DEPTH=2; SEED_MIN=0.60; ASSOC_MAX=64
|
||||
def assoc(seeds, s):
|
||||
act={x:1.0 for x in seeds}; seen={x:2 for x in seeds}
|
||||
Q=[(x,0) for x in seeds]; h=0
|
||||
while h<len(Q):
|
||||
cur,hop=Q[h]; h+=1
|
||||
if hop>=DEPTH: continue
|
||||
p=act[cur]
|
||||
for oid,w in adj.get(cur,()):
|
||||
n=N.get(oid)
|
||||
if not n or n.get('node_type') in ('Tag','InternalStateEvent'): continue
|
||||
na=p*w*DECAY*float(n.get('salience') or 0.0)
|
||||
if na<FIRE: continue
|
||||
if oid in seen and na<=act.get(oid,0): continue
|
||||
act[oid]=na
|
||||
if oid not in seen: seen[oid]=1
|
||||
Q.append((oid,hop+1))
|
||||
out=[]
|
||||
for k,v in seen.items():
|
||||
if v!=1 or k not in eidx: continue
|
||||
c=float(s[eidx[k]])
|
||||
if c<=0: continue
|
||||
out.append((c,k))
|
||||
out.sort(reverse=True)
|
||||
return [k for c,k in out[:ASSOC_MAX]]
|
||||
def inter3(L,S,A,lim=10):
|
||||
out=[]; li=si=ai=0
|
||||
while len(out)<lim and (li<len(L) or si<len(S) or ai<len(A)):
|
||||
if li<len(L):
|
||||
if L[li] not in out: out.append(L[li])
|
||||
li+=1
|
||||
if len(out)>=lim: break
|
||||
if si<len(S):
|
||||
if S[si] not in out: out.append(S[si])
|
||||
si+=1
|
||||
if len(out)>=lim: break
|
||||
if ai<len(A):
|
||||
if A[ai] not in out: out.append(A[ai])
|
||||
ai+=1
|
||||
return out
|
||||
def run(mode, guard, use_main_lex=False):
|
||||
res={}; legs={}
|
||||
for qid,q in gold.items():
|
||||
v=emb(q['query']); s=M@v; s[~np.isfinite(s)]=-1
|
||||
L = LEXMAIN[qid][:10] if use_main_lex else lexleg(q['query'], mode, guard)
|
||||
ordr=np.argsort(-s)
|
||||
S=[eids[j] for j in ordr[:10] if s[j]>SEED_MIN]
|
||||
if guard: S=[x for x in S if PRINT.match(x or '')]
|
||||
seeds=[x for x in L[:3] if x in N]
|
||||
seeds=seeds+[eids[j] for j in ordr[:8] if eids[j] in N and eids[j] not in seeds and (not guard or PRINT.match(eids[j] or ''))]
|
||||
A=assoc(seeds,s) if seeds else []
|
||||
if guard: A=[x for x in A if PRINT.match(x or '')]
|
||||
res[qid]=inter3(L,S,A); legs[qid]=(L,S,A)
|
||||
return res,legs
|
||||
def score(res,label,verbose=False):
|
||||
det={}
|
||||
for qid,q in gold.items():
|
||||
out=res[qid][:5]
|
||||
if q['category']=='nonsense': ok=(len(res[qid])==0)
|
||||
elif q['category']=='superseded':
|
||||
must=q.get('must_outrank') or {}; ok=False
|
||||
for good,bad in (must.items() if isinstance(must,dict) else []):
|
||||
ok = good in res[qid] and (bad not in res[qid] or res[qid].index(good)<res[qid].index(bad))
|
||||
if not must: ok=any(r in out for r in q['relevant'])
|
||||
else: ok=any(r in out for r in q['relevant'])
|
||||
det[qid]=ok
|
||||
print("%-28s outcome-true=%d/38"%(label,sum(det.values())))
|
||||
return det
|
||||
if __name__=="__main__":
|
||||
base,_=run('tokcount',False,use_main_lex=True); b=score(base,'BASELINE semseed(real lex)')
|
||||
variants=[('tokcount',False,'replica: tokcount,noguard'),
|
||||
('tokcount',True ,'A: tokcount + idguard'),
|
||||
('bm25', False,'B: bm25 only'),
|
||||
('bm25', True ,'C: bm25 + idguard')]
|
||||
dets={}
|
||||
for m,g,lab in variants:
|
||||
r,_=run(m,g); dets[lab]=score(r,lab)
|
||||
dd=[q for q in gold if dets[lab][q]!=b[q]]
|
||||
print(" vs BASELINE moved=%d gains=%s losses=%s"%(len(dd),[q for q in dd if dets[lab][q]],[q for q in dd if not dets[lab][q]]))
|
||||
Reference in New Issue
Block a user